Studies on ligand-based pharmacophore modeling approach in identifying potent future EGFR inhibitors

Epidermal growth factor receptor (EGFR) is a validated drug target for cancer chemotherapy. Mutations in EGFR are directly linked with the development of drug resistance and this has led for the development of newer drugs in quest for more efficacious inhibitors. The current research is focused on identifying potential and safe molecules as EGFR inhibitors by using both structure and ligand based computational approaches. In quest for finding newer moieties, we have developed a pharmacophore model utilizing drugs like lazertinib, osimertinib, nazartinib, avitinib, afatininb, and talazoparib that are known to inhibit EGFR along with their downstream signaling. Ligand-based pharmacophore model have been developed to screen the ZINC database through ZINCPharmer webserver. The server has identified 9482 best possible ligands with high pharmacophoric similarity i.e., RMSD value less than 0.2 Å. The top 10 ligands with the criteria of dock score(s) and interactions were further subjected to in silico ADMET studies giving two plausible ligands that were further subjected to Molecular Dynamics and MM/PBSA free energy calculations to ensure stability to the target site. Results deduced by in silico work in the current study may be corroborated biologically in the future. The current work, therefore, provides ample opportunity for computational and medicinal chemists to work in allied areas to facilitate the design and development of novel and more efficacious EGFR inhibitors for future experimental studies. [Display omitted] •The aberrant activity of epidermal growth factor (EGFR) has been seen in numerous cancers.•EGFR inhibition is seen as a vital mechanistic insight for numerous approved clinical candidates and those that are having preclinical status.•Resistance and toxicities in existing drug candidates have led researcher to explore newer pharmacophore for development of EGFR inhibitors.•We did Pharmacophore modeling followed by MD simulation to identify leads for plausible EGFR inhibition.•Analysis revealed that result compounds ZINC20617334 and ZINC68601159 were identified as the hit molecules and may be corroborated for their biological assets in future.